Research Data Scientist

Overview

🔍Dean of Research, Stanford, California, United States📁Research📅Dec 13, 2024 Post Date📅105424 Requisition #This is a 3-year fixed term appointment. Stanford Data Science This position is part of a new initiative incubated within Stanford Data Science, part of the Vice Provost for Research / Dean of Research. Stanford Data Science (SDS) is a dynamic and rapidly growing unit within the VP/Dean of Research.

For more than five years, SDS has sought to advance data science and its application to all fields of study. Our community ranges broadly across all seven schools on campus, consisting of esteemed alumni, world class faculty, post-doctoral fellows and PhD students, dynamic staff and administrators. In realizing our mission, our staff are critical to supporting our organization’s goals and enabling Stanford faculty and students to accomplish their mission conducting cutting-edge research and innovation around how we learn from data, the tools we use, and the new methods needed to tackle the data-intensive future.

This role requires a deep understanding of computational and data science, machine learning, and the scientific process. It also demands the ability to leverage high-performance GPU computing to efficiently process and analyze large datasets. The successful candidate will collaborate closely with Stanford faculty and research groups to design, implement, and refine GPU-accelerated data processing pipelines. They will also contribute to scientific codes using machine learning, statistical analysis, and computation to address complex research challenges.

Additionally, the data scientist will contribute to the development of novel computational methods ranging from biological data analysis to simulation of physical systems via digital twins. Beyond technical expertise, the Research Data Scientist will act as a bridge between Marlowe and the broader research community. They will guide researchers in adapting their applications to Marlowe’s GPU-powered infrastructure by providing technical consultation, creating training materials, and leading workshops.

The ideal candidate will have a strong background in both data science and GPU-centric computational techniques, combined with a passion for fostering collaboration and pushing the boundaries of interdisciplinary research. This position offers an exceptional opportunity to drive transformational research and establish Marlowe as a cornerstone of Stanford’s efforts in pioneering discovery. Remote work for the Research Data Scientist position will be considered.

The Research Data Scientist may be asked to attend certain in-person work events during the year regardless of remote status.

CORE DUTIES

• Code Architecture for GPU Computation:
  Collaborate with Principal Investigators (PIs) and research groups to architect and optimize GPU-accelerated pipelines.
• Develop innovative computational methodologies.
• Co-author resulting research publications.
• Algorithm Development and Data Management:
  Design advanced data movement strategies to minimize memory bottlenecks between CPU and GPU, including real-time data streaming methods for scientific applications.
• Partner with research teams to design novel algorithms and develop high-quality, reusable software to accelerate complex research projects.
• Research Support and Software Infrastructure:
  Assist PIs in applying for supercomputing resources at national centers once projects are scaled and workloads are appropriate. Offer guidance on maximizing efficiency of large-scale computational experiments.
• Install, configure, and maintain software stacks for core research functions.
• Training and Mentorship:
  Design and lead hands-on workshops, and interdisciplinary courses focused on GPU-centric research in fields such as computational biology, NLP and image analysis. Mentor graduate students, postdocs and early-career researchers in computational techniques and research methodologies.
• Open Science and Research Continuity:
  Integrate open science principles into research workflows, including software for data and computational provenance. Design systems to manage inputs, outputs, and provenance to meet NIH, NSF,…